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Article

A Simple, Fully Automated Shoreline Detection Algorithm for High-Resolution Multi-Spectral Imagery

Lyles School of Civil Engineering, Purdue University, 550 Stadium Mall Drive, West Lafayette, IN 47907-2051, USA
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Academic Editors: Chris Blenkinsopp and Katherine Brodie
Remote Sens. 2022, 14(3), 557; https://doi.org/10.3390/rs14030557
Received: 24 December 2021 / Revised: 19 January 2022 / Accepted: 21 January 2022 / Published: 25 January 2022
(This article belongs to the Special Issue New Advances in Coastal Processes and Dynamics Using LiDAR)
This paper develops and validates a new fully automated procedure for shoreline delineation from high-resolution multispectral satellite images. The model is based on a new water–land index, the Direct Difference Water Index (DDWI). A new technique based on the buffer overlay method is also presented to determine the shoreline changes from different satellite images and obtain a time series for the shoreline changes. The shoreline detection model was applied to imagery from multiple satellites and validated to have sub-pixel accuracy using beach survey data that were collected from the Lake Michigan (USA) shoreline using a novel backpack-based LiDAR system. The model was also applied to 132 satellite images of a Lake Michigan beach over a three-year period and detected the shoreline accurately, with a >99% success rate. The model out-performed other existing shoreline detection algorithms based on different water indices and clustering techniques. The resolution shoreline position timeseries is the first satellite image-extracted dataset of its kind in terms of its high spatial and temporal resolution, and paves the road to obtaining other high-temporal-resolution datasets to refine models of beaches worldwide. View Full-Text
Keywords: shoreline detection; shoreline evolution; shoreline timeseries; water index; LiDAR shoreline detection; shoreline evolution; shoreline timeseries; water index; LiDAR
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MDPI and ACS Style

Abdelhady, H.U.; Troy, C.D.; Habib, A.; Manish, R. A Simple, Fully Automated Shoreline Detection Algorithm for High-Resolution Multi-Spectral Imagery. Remote Sens. 2022, 14, 557. https://doi.org/10.3390/rs14030557

AMA Style

Abdelhady HU, Troy CD, Habib A, Manish R. A Simple, Fully Automated Shoreline Detection Algorithm for High-Resolution Multi-Spectral Imagery. Remote Sensing. 2022; 14(3):557. https://doi.org/10.3390/rs14030557

Chicago/Turabian Style

Abdelhady, Hazem U., Cary D. Troy, Ayman Habib, and Raja Manish. 2022. "A Simple, Fully Automated Shoreline Detection Algorithm for High-Resolution Multi-Spectral Imagery" Remote Sensing 14, no. 3: 557. https://doi.org/10.3390/rs14030557

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